I just dump all user messages from all sessions in a project into a flat .md file and have agents synthesize the user's intent. Then, using that extracted intent, the agents review code and tests. I call this a retro/reflection pass. It checks whether the code matches the intent and whether the tests match the code.

Compactly formatted user messages are something an agent can ingest in a few minutes, even if they are thousands of lines long. And the quality of those messages is great: they don't track what the agent does well, only what changes and what breaks.

Having this top-down view helps a lot. Usually, within a session and deep into a task, the agent loses the global perspective and optimizes for local success. I find it weird there is no harness that treats user messages as high value signal (except my own, of course, I have it, https://github.com/horiacristescu/playbook-harness).

Keeping all the specifications and user discussion does create more context, which is useful for AI.

However, I'd bring in Brooks discussion on essential and accidental complexity. In other words, there being No Silver Bullet https://www.cs.unc.edu/techreports/86-020.pdf

The problem with specification and user discussion is they still have errors that code has. But unlike code, there are no tests to confirm correctness.

So now we have a definition of the system in a non-exact language with no ability to test to confirm it's correctness. The code holds the essential complexity and now we are adding accidental complexity on top to manage.

Again agree the specifications and user discussion provides context for the AI. However, a well written test suite provides similar context that can actually confirm correctness of the system.

However, saying all the above. Focus of ImpactGate ( https://impactgate.officefloor.net ) is about erosion of the code, not correctness.